Header

UZH-Logo

Maintenance Infos

Using imaging spectroscopy to predict above-ground plant biomass in alpine grasslands grazed by large ungulates


Schweiger, Anna K; Risch, Anita C; Damm, Alexander; Kneubühler, Mathias; Haller, Rudolf; Schaepman, Michael E; Schütz, Martin (2015). Using imaging spectroscopy to predict above-ground plant biomass in alpine grasslands grazed by large ungulates. Journal of Vegetation Science, 26(1):175-190.

Abstract

Aims: Imaging spectroscopy enables measurement of vegetation optical properties to predict vegetation characteristics that are important for a wide range of ecological applications. Our aim was to predict fresh above-ground biomass of heterogeneous alpine grasslands in two areas and at two ecological scales. We assessed model plausibility for an intensively studied alpine grassland site (plant community scale) having distinct biomass and ungulate grazing patterns.
Location: Alpine grasslands in the Swiss National Park.
Methods: Biomass data were collected in 51 plots and combined with imaging spectroscopy data to establish simple ratio models. We analysed the predictive power and transferability of models developed in two areas (Val Trupchun, Il Fuorn) and at two ecological scales (regional, local). In a next step, we compared our results to the broadband normalized difference vegetation index (NDVI). Finally, we assessed the correlations between model predictions and plant biomass distribution at the plant community scale.
Results: The best local simple ratio models yielded a model fit of R² = 0.60 and R² = 0.30, respectively, the best regional model a fit of R² = 0.44. NDVI model performance was weaker for the regional and one local area, but slightly better for the other local area. However, at the plant community scale only the local model showed a significant positive correlation (Rs = 0.39) with the known biomass distribution. Further, predictive power decreased when models were transferred from one local area to another or from one ecological scale to another.
Conclusions: Our study demonstrated that imaging spectroscopy is generally useful to predict above-ground plant biomass in alpine grasslands with distinct grazing patterns. Site-specific local models based on simple ratio indices performed better than the NDVI or regional models, suggesting that standardized approaches might not be adequate, particularly in heterogeneous grasslands inhabited by large ungulates. We emphasize the importance of collecting ground reference data covering the expected range of productivity and plant species composition. Moreover, plant community-scale data from a previous study proved to be extremely valuable to test model plausibility.

Abstract

Aims: Imaging spectroscopy enables measurement of vegetation optical properties to predict vegetation characteristics that are important for a wide range of ecological applications. Our aim was to predict fresh above-ground biomass of heterogeneous alpine grasslands in two areas and at two ecological scales. We assessed model plausibility for an intensively studied alpine grassland site (plant community scale) having distinct biomass and ungulate grazing patterns.
Location: Alpine grasslands in the Swiss National Park.
Methods: Biomass data were collected in 51 plots and combined with imaging spectroscopy data to establish simple ratio models. We analysed the predictive power and transferability of models developed in two areas (Val Trupchun, Il Fuorn) and at two ecological scales (regional, local). In a next step, we compared our results to the broadband normalized difference vegetation index (NDVI). Finally, we assessed the correlations between model predictions and plant biomass distribution at the plant community scale.
Results: The best local simple ratio models yielded a model fit of R² = 0.60 and R² = 0.30, respectively, the best regional model a fit of R² = 0.44. NDVI model performance was weaker for the regional and one local area, but slightly better for the other local area. However, at the plant community scale only the local model showed a significant positive correlation (Rs = 0.39) with the known biomass distribution. Further, predictive power decreased when models were transferred from one local area to another or from one ecological scale to another.
Conclusions: Our study demonstrated that imaging spectroscopy is generally useful to predict above-ground plant biomass in alpine grasslands with distinct grazing patterns. Site-specific local models based on simple ratio indices performed better than the NDVI or regional models, suggesting that standardized approaches might not be adequate, particularly in heterogeneous grasslands inhabited by large ungulates. We emphasize the importance of collecting ground reference data covering the expected range of productivity and plant species composition. Moreover, plant community-scale data from a previous study proved to be extremely valuable to test model plausibility.

Statistics

Citations

11 citations in Web of Science®
12 citations in Scopus®
Google Scholar™

Altmetrics

Downloads

5 downloads since deposited on 26 Aug 2014
0 downloads since 12 months
Detailed statistics

Additional indexing

Item Type:Journal Article, refereed, original work
Communities & Collections:07 Faculty of Science > Institute of Geography
Dewey Decimal Classification:910 Geography & travel
Language:English
Date:2015
Deposited On:26 Aug 2014 15:44
Last Modified:08 Dec 2017 06:58
Publisher:Wiley-Blackwell Publishing, Inc.
ISSN:1100-9233
Publisher DOI:https://doi.org/10.1111/jvs.12214

Download